An Epithelial–Mesenchymal Transition Gene Signature Predicts Resistance to EGFR and PI3K Inhibitors and Identifies Axl as a Therapeutic Target for Overcoming EGFR Inhibitor Resistance

Abstract
Purpose: Epithelial–mesenchymal transition (EMT) has been associated with metastatic spread and EGF receptor (EGFR) inhibitor resistance. We developed and validated a robust 76-gene EMT signature using gene expression profiles from four platforms using non–small cell lung carcinoma (NSCLC) cell lines and patients treated in the Biomarker-Integrated Approaches of Targeted Therapy for Lung Cancer Elimination (BATTLE) study.
Experimental Design: We conducted an integrated gene expression, proteomic, and drug response analysis using cell lines and tumors from patients with NSCLC. A 76-gene EMT signature was developed and validated using gene expression profiles from four microarray platforms of NSCLC cell lines and patients treated in the BATTLE study, and potential therapeutic targets associated with EMT were identified.
Results: Compared with epithelial cells, mesenchymal cells showed significantly greater resistance to EGFR and PI3K/Akt pathway inhibitors, independent of EGFR mutation status, but more sensitivity to certain chemotherapies. Mesenchymal cells also expressed increased levels of the receptor tyrosine kinase Axl and showed a trend toward greater sensitivity to the Axl inhibitor SGI-7079, whereas the combination of SGI-7079 with erlotinib reversed erlotinib resistance in mesenchymal lines expressing Axl and in a xenograft model of mesenchymal NSCLC. In patients with NSCLC, the EMT signature predicted 8-week disease control in patients receiving erlotinib but not other therapies.
Conclusion: We have developed a robust EMT signature that predicts resistance to EGFR and PI3K/Akt inhibitors, highlights different patterns of drug responsiveness for epithelial and mesenchymal cells, and identifies Axl as a potential therapeutic target for overcoming EGFR inhibitor resistance associated with the mesenchymal phenotype. Clin Cancer Res; 19(1); 1–12. ©2012 AACR.
Footnotes
Note: Supplementary data for this article are available at Clinical Cancer Research Online (http://clincancerres.aacrjournals.org/).
Affymetrix microarray results from the cell line training set were previously published and archived at the Gene Expression Omnibus repository (http://www.ncbi.nlm.nih.gov/geo/, GEO accession GSE4824).
Illumina v2 (GSE32989) and v3 (GSE32036) results have been deposited in the GEO repository and are available at the following links.
Illumina v2: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?token=lxatjamqwakaidw&acc=GSE32989.
Illumina v3: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?token=pfiphqkackiyubo&acc=GSE32036.
BATTLE array results have been deposited in the GEO repository (GSE33072) and are available at the following links: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?token=xfwnxqsygocaajg&acc=GSE33072.
- Received May 15, 2012.
- Revision received September 25, 2012.
- Accepted October 9, 2012.
- ©2012 American Association for Cancer Research.
This OnlineFirst version was published on December 20, 2012
doi: 10.1158/1078-0432.CCR-12-1558